Traditional forecasting treats over- and under-predictions equally, but in real-world scenarios like financial markets, the costs can differ significantly. Quantile forecasting addresses this by estimating confidence intervals, offering a nuanced view of uncertainty. In my latest post, I explore how this method works and cover its advantages.